Scielo RSS <![CDATA[Journal of the Southern African Institute of Mining and Metallurgy]]> vol. 115 num. 6 lang. en <![CDATA[SciELO Logo]]> <![CDATA[<b>Journal Comment</b>]]> <![CDATA[<b>President's Corner</b>]]> <![CDATA[<b>Report back on the ITA 2015 general assembly forty-first annual meeting held in Dubrovnik, Croatia</b>]]> <![CDATA[<b>The SAIMM Young Professionals' Council (SAIMM-YPC)</b>]]> <![CDATA[<b>Predicting the probability of Iron-Rich Ultramafic Pegmatite (IRUP) in the Merensky Reef at Lonmin's Karee Mine</b>]]> IRUP is an iron-rich ultramafic pegmatite rock that formed due to hot iron-rich fluids and gases replacing local stratigraphic zones of the Bushveld Complex. This study focuses on the estimation of the probability of IRUP occurrence on the Merensky Reef at the Marikana Karee Mine. A 2.15 million centare IRUP-rich domain at the Karee Mine was initially defined from the interpretation of a surface aeromagnetic anomaly, and exposures in the mine workings. Surface boreholes (spaced 250-500 m apart) within this IRUP domain contain approximately equal numbers of IRUP-replaced and IRUP-free intersections. Owing to the uncertainty in the continuity of the IRUP alteration (a result of the wide borehole spacing), the risk associated with the development of mining infrastructure within this domain is unquantifiable. Semi-quantitative data comprising visual estimates of IRUP replacement from reef development mapping data and surface borehole reef intersections was interpolated into blocks using indicator kriging estimation. Comparative analyses of the estimate of IRUP occurrences were made by changing the block size and declustering the data systematically. Reconciliations of the probability of IRUP predicted from the block models derived from the different data-sets and sequential indicator simulation models were analysed for four mining study blocks. A quantitative approach to modelling the occurrence of IRUP can be an additional tool for refining the estimate of the geological losses that inform the mine plan in such high-risk zones. <![CDATA[<b>Tough choices facing the South African mining industry</b>]]> Strategy is about making choices. Mining companies choose to do certain things and not to do other things. Mining is a long-term business, and the choices made typically have large investments attached to them, long payback periods, and significant socio-economic consequences. In today's uncertain world, it is important to make the right choices. The mining industry in South Africa finds itself in a difficult situation. Operating conditions are tough, the socio-political environment is complex, and financial performance is under pressure. The choices made by all the stakeholders in this industry in the short term will shape the future of the industry. This paper characterizes some of the big, difficult decisions faced by the mining industry in the South African context, and discusses how these decisions could be approached in a fact-based and robust way. <![CDATA[<b>Crush pillar support - designing for controlled pillar failure</b>]]> The aim of any mine design is to ensure that the excavations remain stable for the period they will be in use. Various pillar systems are used to ensure that underground stopes remain stable and that mining activities do not affect the surface infrastructure through either surface subsidence or seismicity. Intermediate-depth platinum mines make use of in-stope pillars designed to fail while the pillars are being cut at the mining face. The pillar stress exceeds the loading capacity and the pillars crush as a result. The aim of the paper is to provide an overview of in-stope crush pillars. This will include the application, behaviour, function, mechanism, impact, and design of a crush pillar system. <![CDATA[<b>The application of pumpable emulsions in narrow-reef stoping</b>]]> Pumpable emulsion explosives have been available to surface and underground massive mining operations for decades, and their unique properties offer significant advantages in terms of improved safety, reliability, and performance. However, the benefits of pumpable emulsions have been unavailable to narrow-reef mining operations due to the lack of technology necessary for their successful implementation in this challenging environment. Despite efforts to promote and enhance the safety and performance of bulk emulsions for narrow-reef stoping, little research has been undertaken to advance the pump technologies required for their implementation. This has resulted in a gap in knowledge and technology, and as a consequence the successful implementation of a pumpable emulsion system has consistently eluded the narrow-reef environment. The purpose of the following investigation was to evaluate the viability of pumpable emulsion explosives for use in South African narrow-reef mining operations. By approaching the problem from multiple perspectives, this research aimed firstly to propose a theoretical framework and suite of equipment suitable for the implementation of pumpable emulsions within the narrow-reef environment. Through the development of this suite of pumpable emulsion technology, tests could be undertaken on the proposed narrow-reef emulsion formulation and pumpable emulsion technology to obtain the necessary understanding of the performance of the system under controlled operating conditions prior to its implementation in the broader mining industry. <![CDATA[<b>Corrosion resistance of laser-cladded 304L stainless steel enriched with ruthenium additions exposed to sulphuric acid and sodium chloride media</b>]]> The corrosion behaviour of 304L stainless steel laser-cladded with various amounts of ruthenium (Ru) was evaluated in solutions of sulphuric acid and sulphuric acid plus sodium chloride at 25°C and 45°C by open-circuit potential and cyclic potentiodynamic polarization tests. In general, the addition of Ru to the stainless steel increased its corrosion resistance in 1 M H2SO4, as well as in 1 M H2SO4 plus 1 wt% NaCl. This was observed for a number of parameters such as corrosion rate, corrosion potential, open-circuit potential, and current density. However, increasing the amount of Ru added beyond a certain level did not result in further improvement in corrosion protection. For each environment there is an optimal Ru concentration for the best corrosion protection. For example, in 1 M H2SO4 at 25°C, 2.44 wt% Ru shows the least active surface in terms of corrosion. Further research into ruthenium coatings on stainless steels is recommended. <![CDATA[<b>Fire and brimstone: The roasting of a Merensky PGM concentrate</b>]]> <![CDATA[<b>Strategic and tactical requirements of a mining long-term plan</b>]]> The long-term plan (LTP) in a mineral resource company is defined by the quality of the mineral resource and represents the result of a series of trade-offs to fulfil internal organizational as well as external business and legislative requirements, ensuring ultimate delivery on the defined organizational strategy. The LTP should as a whole align to a coherent and well-defined organizational strategy, working towards a clearly defined objective while still allowing a tactical response to short-term requirements of the organization. The ability to respond tactically to changes in environment, like the unprecedented five-month strike in 2014 on the platinum belt following the 2012 Marikana incident, is a measure of the flexibility of the plan given the agreed strategy. This paper describes the Lonmin process of linking company strategy with long-term planning, tactical planning, and the execution of the plan through an annual planning cycle to maximize organizational flexibility. This flexibility enables mining companies to respond to the many internal and external forces that impact on both strategy formulation and delivery of results that meet shareholder expectations. <![CDATA[<b>Integration of imprecise and biased data into mineral resource estimates</b>]]> Mineral resources are typically informed by multiple data sources of varying reliability throughout a mining project life cycle. Abundant data which are imprecise or biased or both ('secondary data') are often excluded from mineral resource estimations (the 'base case') under an intuitive, but usually untested, assumption that this data may reduce the estimation precision, bias the estimate, or both. This paper demonstrates that the assumption is often wasteful and realized only if the secondary data are naïvely integrated into the estimation. A number of specialized geostatistical tools are available to extract maximum value from secondary information which are imprecise or biased or both; this paper evaluates cokriging (CK), multicollocated cokriging (MCCK), and ordinary kriging with variance of measurement error (OKVME). Where abundant imprecise but unbiased secondary data are available, integration using OKVME is recommended. This re-appropriates kriging weights from less precise to more precise data locations, improving the estimation precision compared to the base case and to Ordinary Kriging (OK) of a pooled data-set. If abundant secondary data are biased and imprecise, integration through CK is recommended as the biased data are zero-sum weighted. CK consequently provides an unbiased estimate with some improvement in estimation precision compared to the base case. <![CDATA[<b>Stochastic simulation for budget prediction for large surface mines in the South African mining industry</b>]]> This article investigates the complex problem of a budgeting process for a large mining operation. Strict adherence to budget infers that financial results align with goals. In reality, the budget is not a predetermined entity but emerges as the sum of the enterprise's operational plans. These are highly interdependent, being influenced by unforeseeable events and operational decision-making. Limitations of stochastic simulations, normally applied in the project environment but not in budgeting, are examined and a model enabling their application is proposed. A better understanding of budget failure in large mines emerges, showing that the budget should be viewed as a probability distribution rather than a single deterministic value. The strength of the model application lies with the combining of stochastic simulation, probability theory, financial budgeting, and practical scheduling to predict budget achievement, reflected as a probability distribution. The principal finding is the interpretation of the risk associated with, and constraints pertaining to, the budget. The model utilizes a four-dimensional (space and time) schedule, linking key drivers through activity-based costing to the budget. It offers a highly expressive account of deduction regarding fund application for budget achievement, emphasizing that 'it is better to be approximately right than precisely wrong'. <![CDATA[<b>Q-coda estimation in the Kaapvaal Craton</b>]]> The Q-coda method for estimating the quality factor Q(f)= Qo(f)n was used to characterize seismic wave attenuation in a region of the Kaapvaal Craton that includes the mining areas of the Bushveld Complex and Witwatersrand Basin. Seismic waveform data, collected by locally distant stations of the South African National Seismograph Network (SANSN), consisted of mining-related events with magnitudes ranging from M L 1.8 to M L 4. Q was calculated for nine different source-receiver pairs spanning the study region. A weighted average Q based on the number of available data gave an estimated attenuation relation for the study region of Q(f) = 327f0.81. <![CDATA[<b>Geometallurgical model of a copper sulphide mine for long-term planning</b>]]> One of the main problems related to mining investment decisions is the use of accurate prediction models. Metallurgical recovery is a major source of variability, and in this regard, the Chuquicamata processing plant recovery was modelled as a function of geomining-metallurgical data and ore characteristics obtained from a historical database. In particular, the data-set gathered contains information related to feed grades, ore hardness, particle size, mineralogy, pH, and flotation reagents. A systemic approach was applied to fit a multivariate regression model representing the copper recovery in the plant. The systemic approach consists of an initial projection of the characteristic grinding product size (P80), based upon energy consumption at the particle size reduction step, followed by a flotation recovery model. The model allows for an improvement in the investment decision process by predicting performance and risk. The final geometallurgical model uses eight operational variables and is a significant improvement over conventional prediction models. A validation was performed using a recent data-set, and this showed a high correlation coefficient with a low mean absolute error, which reveals that the geomet-allurgical model is able to predict, with acceptable accuracy, the actual copper recovery in the plant. <![CDATA[<b>Introduction to the production of clean steel</b>]]> This paper introduces the concept of clean steel production from a pyrometallurgist's perspective to the broader metallurgical community. A simplistic overview of the steelmaking process from iron ore to car body manufacturing is followed by an introduction to the South African steel industry and the technologies that it utilizes. The process is illustrated by an overview of the flow sheet and technologies for the production of clean steel at Saldanha Steel, South Africa.